A full life cycle biological clock based on routine clinical data and its impact in health and diseases

Aging research has primarily focused on adult aging clocks, leaving a critical gap in understanding a biological clock across the full life cycle, particularly during infancy and childhood. Here we introduce LifeClock, a biological clock model that predicts biological age across all life stages using routine electronic health records and laboratory test data. To enhance individualized predictions, we integrated virtual patient representations from 24,633,025 heterogeneous longitudinal clinical visits across 9,680,764 individuals and projected them into a latent space. Our approach leverages EHRFormer, a time-series transformer-based model, to analyze developmental and aging dynamics with high precision and develop accurate biological age clocks spanning infancy to old age. Our findings reveal distinct biological clock patterns across different life stages. The pediatric clock is strongly associated with children's development and accurately predicts current and future risks of major pediatric diseases, including malnutrition, growth and developmental abnormalities. The adult clock is strongly associated with aging and accurately predicts current and future risks of major age-related diseases, such as diabetes, renal failure, stroke and cardiovascular diseases. This work therefore distinguishes pediatric development from adult aging, establishing a novel framework to advance precision health by leveraging routine clinical data across the entire lifespan.

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Publication Details

Journal
Nature Medicine
Published
2025-10-27
DOI
https://doi.org/10.1038/s41591-025-04006-w
Citations
7
Primary Topic
Circadian rhythm and melatonin
Type
article
Field-Weighted Citation Impact
6.40
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article

A full life cycle biological clock based on routine clinical data and its impact in health and diseases

Yun Yin, Sian Liu, Xian Shen, Wen-Yang Lu et al.
7 citations
Nature Medicine
Circadian rhythm and melatonin
6.40
article

A full life cycle biological clock based on routine clinical data and its impact in health and diseases

Yun Yin, Sian Liu, Xian Shen, Wen-Yang Lu, B Li, Jinghang Li, Shengwei Jin, Io Nam Wong, Ying‐Jie Zhu, Eric K. Oermann, Alexandre Loupy, Zhe Feng, Tian Zhong, Xiaoying Huang, Changxi Hu, Mingqi Yang, Gen Li, Xiaohong Chen, Gang Chen, Li Liu, Kang Zhang, Ping Li, Kun Li, Qiang Hou, Huiyan Xu, Linling Cheng, Fanxin Zeng, Xiangmei Chen, Winston Wang, Zhenqi Li, Yiwen Sun, Meihao Wang, Wei Wu, Fei Liu, Kai Wang, Zixing Zou, Zhuo Sun
article en
7 citations

Abstract

Aging research has primarily focused on adult aging clocks, leaving a critical gap in understanding a biological clock across the full life cycle, particularly during infancy and childhood. Here we introduce LifeClock, a biological clock model that predicts biological age across all life stages using routine electronic health records and laboratory test data. To enhance individualized predictions, we integrated virtual patient representations from 24,633,025 heterogeneous longitudinal clinical visits across 9,680,764 individuals and projected them into a latent space. Our approach leverages EHRFormer, a time-series transformer-based model, to analyze developmental and aging dynamics with high precision and develop accurate biological age clocks spanning infancy to old age. Our findings reveal distinct biological clock patterns across different life stages. The pediatric clock is strongly associated with children's development and accurately predicts current and future risks of major pediatric diseases, including malnutrition, growth and developmental abnormalities. The adult clock is strongly associated with aging and accurately predicts current and future risks of major age-related diseases, such as diabetes, renal failure, stroke and cardiovascular diseases. This work therefore distinguishes pediatric development from adult aging, establishing a novel framework to advance precision health by leveraging routine clinical data across the entire lifespan.

Nature MedicineVol. 31(12)
Macau University of Science and Technology (MO), Inserm (FR), University of Pittsburgh (US), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking University (CN), University of Macau (MO), Université Paris Cité (FR), Wenzhou Medical University (CN), Nepean Hospital (AU), First Affiliated Hospital of Wenzhou Medical University (CN), King Center (US), Chinese PLA General Hospital (CN), NYU Langone Health (US), Affiliated Eye Hospital of Wenzhou Medical College (CN), National Cancer Center (US), Guangzhou Experimental Station (CN), Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University (CN), Zhuhai People's Hospital (CN), Mayo Clinic in Arizona (US), Paris Cardiovascular Research Center (FR), Changzhou Third People's Hospital (CN), Center for Life Sciences (CN), Dazhou Central Hospital (CN), Hospital Conde S. Januário (CN), Southern Medical University (CN), City University of Macau (MO)
Openalex Percentile: Top 3%
Circadian rhythm and melatonin
6.40
DOIOpen Access PDFOpenAlex
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